The current heightened sense of security and declining cost of monitoring equipment have resulted in increased use of surveillance systems using technologies such as closed-circuit television (CCTV). Such systems have the potential to reduce crime, prevent accidents, and generally increase security in a wide variety of environments. Video surveillance systems typically include a series of cameras placed in various locations about an area of interest (e.g., a warehouse, a retail establishment, an office building, an airport, for example). The cameras transmit video feeds back to a central viewing stations (or multiple stations), typically manned by a security officer. The various surveillance feeds are displayed on a series of screens, which are monitored for suspicious activities.
In addition to using CCTV systems at individual locations, there is great interest in using video surveillance and analysis systems to collect data about the behavior of people across multiple locations. For example, a national retail store chain might be interested in the behavior of shoppers in its various stores. While data collected from a single site is useful, the full value of the data is only realized when comparing data from different sites, such as providing insights into how to optimally deploy resources across multiple locations at or within a site to achieve specific goals.
In order to be useful, however, the data from one location should be comparable to data collected at other similar locations. That is, the same events (e.g., “person paused in front of display”) should have a consistent meaning at each location. However, because of non-standard floor-plans, variable camera configurations, and other site differences, the occurrence of an event can appear quite different (from the point-of-view of a surveillance system) at each location. Such differences make it difficult for a single person (e.g., a chief security officer or corporate marketing analyst) to specify an event at the level of detail needed in order to reliably detect the event at multiple disparate locations.
One approach to dealing with the problem of non-uniform locations is to have a global operator interact with a surveillance system at each individual site to define events of interest. While this approach has the advantage that events can be centrally controlled and managed, time and resource constraints prohibit the scalability across many sites. Another approach requires that similar locations across all sites be identical, both in floor-plan and sensor placement. Although this approach allows a global operator to centrally define events of interest and replicate the events across all locations, requiring all locations to be identical is not practical. A third approach places the responsibility of event definition in the hands of local site operators, but such an approach relinquishes any element of centralized control and significantly reduces data consistency across sites.
Unfortunately, none of these approaches is sufficient. What is needed, therefore, is a technique for centrally defining and managing events at a global level while allowing variability among location layouts and camera configurations.